Summary: Tracking, Analysis, and Recognition of Human Gestures in Video
Stan Sclaroff, Margrit Betke, George Kollios,
Jonathan Alon, Vassilis Athitsos, Rui Li, John Magee, Tai-peng Tian
Dept. of Computer Science, Boston University, Boston, MA, 02215, U.S.A
Abstract
An overview of research in automated gesture spotting,
tracking and recognition by the Image and Video Comput-
ing Group at Boston University is given. Approaches for
localization and tracking human hands in video, estimation
of hand shape and upper body pose, tracking head and fa-
cial motion, as well as efficient spotting and recognition of
specific gestures in video streams are summarized. Meth-
ods for efficient dimensionality reduction of gesture time se-
ries, boosting of classifiers for nearest neighbor search in
pose space, and model-based pruning of gesture alignment
hypotheses are described. Algorithms are demonstrated in
three domains: American Sign Language, hand signals like
those employed by flight-directors on airport runways, and
gesture-based interfaces for severely disabled users. The
methods described are general and can be applied in other